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          成都地区对R有兴趣的兄弟姐妹们注意啦！
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            <div class="bbp-reply-header" id="post-217687">
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               2007年1月10日 上午3:27
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              <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/3327/page/2/#post-217687">
               16 楼
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               希望下次聚会可以看到更多热爱R的朋友！
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               2007年1月10日 上午5:22
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              <p>
               我计划一月份，最迟不超过春节，把这本伍德里奇的初级计量教程已有的stata环境下解决的问题统一的用R实现。希望这一实现对学习计量的人有所裨益，也希望可以吸引更多的人来了解和使用R。
              </p>
              <p>
               首先，我需要获得该书的数据；再次要获得网上既有的Stata软件实现的结果：这些不需要一步一步的点击下载，也不需要使用另外的什么专门的下载软件。因为在R中有内置的函数可以完成这项工作，而且非常容易就可以实现了。下面是代码：
               <br/>
               （我们事先必须知道数据文件在网络上的位置，帮助文件在网络上的位置；感谢Denver兄告诉我下载的地址。）
              </p>
              <p>
               # download.file("
               <a class="d4pbbc-url" href="http://fmwww.bc.edu/gstat/examples/wooldridge/wooldridge2.html" rel="nofollow" target="_blank">
                http://fmwww.bc.edu/gstat/examples/wooldridge/wooldridge2.html
               </a>
               ","E:/ch2.html")
               <br/>
               # 设置下载路径名称，保存到本地文件的名称
               <br/>
               # 使用setwd设置相应帮助文件下载后的路径，比如setwd("E:/WooldHelp/")
               <br/>
               webpath &lt;- "
               <a class="d4pbbc-url" href="http://fmwww.bc.edu/gstat/examples/wooldridge/wooldridge" rel="nofollow" target="_blank">
                http://fmwww.bc.edu/gstat/examples/wooldridge/wooldridge
               </a>
               "
               <br/>
               webpath &lt;- paste("\"",webpath,2:18,".html\"",sep="")
               <br/>
               filepath &lt;- paste("\"ch",2:18,".html\"",sep="")
               <br/>
               # 组合成为命令，输出成为R脚本，然后调用source函数运行
               <br/>
               cmd &lt;- paste("download.file(", webpath, ",", filepath, ")\n")
               <br/>
               sink("cmd.r")
               <br/>
               # 这里完全是为了节省code，使用了粗暴的做法，而未进行R语言运算
               <br/>
               cat(cmd)
               <br/>
               sink()
               <br/>
               source("cmd.r")
               <br/>
               file.remove("cmd.r")
               <br/>
               ######################################################################################################
               <br/>
               ######################################################################################################
               <br/>
               # 从web上下载stata数据，使用download.file函数
               <br/>
               # 路径为：
               <a class="d4pbbc-url" href="http://fmwww.bc.edu/ec-p/data/wooldridge/" rel="nofollow" target="_blank">
                http://fmwww.bc.edu/ec-p/data/wooldridge/
               </a>
               <br/>
               # file.names为所有数据的名称
               <br/>
               # 使用setwd设置相应帮助文件下载后的路径，比如setwd("E:/WooldStataData/")
               <br/>
               datapath &lt;- "
               <a class="d4pbbc-url" href="http://fmwww.bc.edu/ec-p/data/wooldridge/" rel="nofollow" target="_blank">
                http://fmwww.bc.edu/ec-p/data/wooldridge/
               </a>
               "
               <br/>
               file.names &lt;- c(
               <br/>
               "401K.DTA" ,    "401KSUBS.DTA", "ADMNREV.DTA",  "affairs.dta",  "airfare.dta",
               <br/>
               "APPLE.DTA",    "ATHLET1.DTA",  "ATHLET2.DTA",
               <br/>
               "ATTEND.DTA"  , "AUDIT.DTA"    ,"BARIUM.DTA" ,  "BWGHT.DTA" ,   "bwght2.dta" ,
               <br/>
               "campus.dta" ,  "CARD.DTA",     "cement.dta" ,
               <br/>
               "CEOSAL1.DTA"  ,"CEOSAL2.DTA"  ,"consump.dta" , "CORN.DTA"  ,   "CPS78_85.DTA",
               <br/>
               "cps91.dta",    "CRIME1.DTA" ,  "CRIME2.DTA" ,
               <br/>
               "CRIME3.DTA"   ,"CRIME4.DTA"   ,"discrim.dta" , "EARNS.DTA" ,   "engin.dta"  ,
               <br/>
               "EZANDERS.DTA" ,"ezunem.dta" ,  "FAIR.DTA"   ,
               <br/>
               "FERTIL1.DTA"  ,"FERTIL2.DTA"  ,"FERTIL3.DTA" , "FISH.DTA"  ,   "FRINGE.DTA" ,
               <br/>
               "GPA1.DTA" ,    "gpa2.dta" ,    "GPA3.DTA"   ,
               <br/>
               "hprice1.dta"  ,"HPRICE2.DTA"  ,"HPRICE3.DTA" , "HSEINV.DTA" ,  "HTV.DTA"    ,
               <br/>
               "INFMRT.DTA" ,  "INJURY.DTA"  , "INTDEF.DTA"  ,
               <br/>
               "INTQRT.DTA"  , "INVEN.DTA"    ,"JTRAIN.DTA" ,  "JTRAIN2.DTA",  "KIELMC.DTA" ,
               <br/>
               "LAWSCH85.DTA" ,"loanapp.dta" , "LOWBRTH.DTA"  ,
               <br/>
               "mathpnl.dta" , "MEAP93.DTA"  , "MLB1.DTA"   ,  "MROZ.DTA"  ,   "MURDER.DTA" ,
               <br/>
               "nbasal.dta"  , "NYSE.DTA" ,    "OPENNESS.DTA" ,
               <br/>
               "PENSION.DTA" , "PHILLIPS.DTA", "PNTSPRD.DTA" , "PRISON.DTA" ,  "PRMINWGE.DTA",
               <br/>
               "RDCHEM.DTA" ,  "rdtelec.dta" , "RECID.DTA"  ,
               <br/>
               "RENTAL.DTA"  , "RETURN.DTA"  , "SAVING.DTA"  , "SLEEP75.DTA" , "SLP75_81.DTA",
               <br/>
               "SMOKE.DTA"  ,  "TRAFFIC1.DTA", "TRAFFIC2.DTA" ,
               <br/>
               "twoyear.dta" , "VOLAT.DTA"   , "VOTE1.DTA"  ,  "VOTE2.DTA" ,   "WAGE1.DTA"  ,
               <br/>
               "WAGE2.DTA" ,   "WAGEPAN.DTA",  "WAGEPRC.DTA" , "wine.dta")
               <br/>
               # 数据集的数量为setnum
               <br/>
               setnum &lt;- length(file.names)
               <br/>
               full.path &lt;- paste(datapath, file.names, sep="")
               <br/>
               for(i in 1:setnum) download.file(full.path[1],paste(file.names
               <em class="d4pbbc-italic">
               </em>
               , sep=""))
              </p>
              <p>
               ######################################################################################################
               <br/>
               # 提取下载后的数据，具体路径设置和下载位置相同
               <br/>
               rm(list=ls(all=T))
               <br/>
               library(foreign)              # 使用read.dta函数直接读取stata数据
               <br/>
               file.names &lt;- dir("E:/AbelRS/WooldridgeBookData/STATA/")
               <br/>
               full.names &lt;- paste("E:/AbelRS/WooldridgeBookData/STATA/", file.names, sep="")
               <br/>
               file.list &lt;- lapply(full.names,read.dta)
               <br/>
               dat.names &lt;- unlist(strsplit(file.names,".",fixed=T))[2*(1:length(file.names))-1]
               <br/>
               names(file.list) &lt;- dat.names
               <br/>
               # 将包含所有数据的列表存储在当前路径下，文件名是DataSets.RData，
               <br/>
               # 全部变换为R可以直接使用的数据了
               <br/>
               # 文件大小和压缩后的dta差不多大
               <br/>
               save("file.list", file="DataSets.RData")
               <br/>
               rm(list=ls(all=T))
               <br/>
               load("E:/AbelRS/WooldridgeBookData/DataSets.RData")
               <br/>
               attach(file.list)           # 加载该列表，使得可以直接调用数据框
              </p>
              <p>
               我们现在一次性的将这些数据文件放在了我们本机硬盘上。当然，可以在需要使用Stata数据的时候逐一下载，比如：
               <br/>
               download.file("
               <a class="d4pbbc-url" href="http://fmwww.bc.edu/ec-p/data/wooldridge/NYSE.dta" rel="nofollow" target="_blank">
                http://fmwww.bc.edu/ec-p/data/wooldridge/NYSE.dta
               </a>
               ", "NYSE.dta")
               <br/>
               # library(foreign)
               <br/>
               NYSE &lt;- read.dta("NYSE.dta")
               <br/>
               attach(NYSE)
              </p>
              <p>
               随后就可以进行我们所需要的分析了……
              </p>
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            <div class="bbp-reply-header" id="post-217724">
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              <span class="bbp-reply-post-date">
               2007年1月10日 上午8:48
              </span>
              <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/3327/page/2/#post-217724">
               18 楼
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               谢益辉
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              <div class="bbp-author-role">
               站长
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              <p>
               呵呵，我曾经也想写点这样的语句用来下载文件，一直也没有付诸实践。
              </p>
              <p>
               这些Stata数据直接用FlashGet批量下载吧：（在本页面上点右键，“用网际快车下载全部链接”，然后“选择特定”，“文件扩展名”选择dta就可以了）
              </p>
              <p>
               <a class="d4pbbc-url" href="http://fmwww.bc.edu/ec-p/data/wooldridge/VOLAT.dta" rel="nofollow" target="_blank">
                http://fmwww.bc.edu/ec-p/data/wooldridge/VOLAT.dta
               </a>
               <br/>
               <a class="d4pbbc-url" href="http://fmwww.bc.edu/ec-p/data/wooldridge/TRAFFIC1.dta" rel="nofollow" target="_blank">
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               2007年1月11日 上午11:42
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              <p>
               R中似乎可以通过XML方面的冬冬来解析链接，自动下载哈，不过用这个的人应该很稀罕了吧。
              </p>
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               2007年1月11日 上午11:46
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              <p>
               鉴于要以Wooldridge初级教程中的示例作为R使用的介绍载体，和Stata的结果对比，特制作了两个函数，用于给出和Stata结果对应的输出。不当之处请诸位指点：
              </p>
              <p>
               abel.summ &lt;- function(x, ci, all=F)
               <br/>
               {
               <br/>
               StatsUniv &lt;- function(x, ci=ci)
               <br/>
               {
               <br/>
               x &lt;- as.vector(x)
               <br/>
               x.lenFull &lt;- length(x)
               <br/>
               x &lt;- x[!is.na(x)]
               <br/>
               x.len &lt;- length(x)
               <br/>
               x.na &lt;- x.lenFull – x.len
               <br/>
               if(missing(ci)) ci &lt;- c(0.025,0.975)
               <br/>
               if(length(ci) != 2)
               <br/>
               {
               <br/>
               ci &lt;- ci[1]
               <br/>
               a &lt;- (1-ci)/2
               <br/>
               ci &lt;- c(a, 1-a)
               <br/>
               }
               <br/>
               pct &lt;- paste(c("LCL","UCL"),":",ci*100, "%",sep="")
               <br/>
               t.Low &lt;- qt(ci[1], df=x.len-1)
               <br/>
               t.Up &lt;- qt(ci[2], df=x.len-1)
              </p>
              <p>
               x.min &lt;- min(x)
               <br/>
               x.max &lt;- max(x)
               <br/>
               x.sum &lt;- sum(x)
               <br/>
               x.mean &lt;- mean(x)
               <br/>
               x.sd &lt;- sd(x)
               <br/>
               x.se &lt;- x.sd/sqrt(x.len-1)
               <br/>
               x.lcl &lt;- x.mean+t.Low*x.se
               <br/>
               x.ucl &lt;- x.mean+t.Up*x.se
               <br/>
               x.skew &lt;- sum((x – x.mean)^3/sqrt(var(x))^3)/x.len
               <br/>
               x.kurt &lt;- sum((x – x.mean)^4/var(x)^2)/x.len – 3
               <br/>
               <br/>
               ans &lt;- c(x.lenFull, x.mean, x.sd, x.min, x.max, x.len, x.na, x.sum, x.se, x.skew, x.kurt, x.lcl, x.ucl)
               <br/>
               ans.names &lt;- c("Nobs", "Mean", "STD", "Min", "Max", "N", "Na", "Sum", "SE", "Skew", "Kurt", pct)
               <br/>
               names(ans) &lt;- ans.names
               <br/>
               ans
               <br/>
               }
               <br/>
               if(missing(ci)) ci &lt;- 0.95
               <br/>
               ans &lt;- t(sapply(x, StatsUniv, ci=ci))
               <br/>
               ans &lt;- as.data.frame(ans)
               <br/>
               if(all) return(ans) else return(ans[,1:5])
               <br/>
               }
              </p>
              <p>
               abel.coef &lt;- function(x, level=0.05)
               <br/>
               {
               <br/>
               if(level&lt;=0 || level&gt;=1) stop("显著水平在0～1之间")
               <br/>
               if(level&gt;0.5) level &lt;- 1-level
               <br/>
               cf &lt;- coef(x)
               <br/>
               se &lt;- sqrt(diag(vcov(x)))
               <br/>
               a &lt;- level/2
               <br/>
               a &lt;- c(a, 1 – a)
               <br/>
               pct &lt;- format(100*a, digits=4)
               <br/>
               df &lt;- df.residual(x)
               <br/>
               fac &lt;- qt(a, df=df)
               <br/>
               ci &lt;- cf + se %o% fac
               <br/>
               t.value &lt;- as.vector(cf)/se
               <br/>
               pr.value &lt;- 2*pt(abs(t.value), df=df, lower.tail=F)
               <br/>
               if (!is.null(names(cf)) &amp;&amp; !is.null(names(se)))
               <br/>
               {
               <br/>
               anames &lt;- names(cf)[names(cf) %in% names(se)]
               <br/>
               cf &lt;- cf[anames]
               <br/>
               se &lt;- se[anames]
               <br/>
               }
               <br/>
               ans.names &lt;- c("Coef.", "S.E.", "t value", "Pr(&gt;|z|)",
               <br/>
               paste(c("Lower", "Upper"),":",pct,"%",sep=""))
               <br/>
               ans &lt;- data.frame(cf, se, t.value, pr.value, ci)
               <br/>
               colnames(ans) &lt;- ans.names
               <br/>
               ans
               <br/>
               }
              </p>
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               2007年1月11日 下午4:22
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              <p>
               要不要到其他地方去啊? 我在南京,也很想有这种活动啊!
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               2007年1月15日 上午4:59
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              <p>
               本月13、14日，在西南财经大学光华楼的2402教室进行了R/S兴趣小组讨论聚会。
              </p>
              <p>
               13日主要讨论了Wooldridge计量教程所有示例使用R实现的工作，为实现示例和习题供需要的特殊的输出和经过简单计算以后整合模型结果的需要，编写了两个函数。
               <br/>
               同时介绍了计量经济学中常常使用到的各种常见的统计模型，并就R中各个建模函数中一般都会存在的参数、结果组成等进行了交流。
              </p>
              <p>
               14日主要讨论了R中实现数据操作的主题：各种对象中条件取子集，抽样，stack，合并等平时经常遇到的情况。该主题将于下次讨论前整理为正式的讲义格式文档发布，便于以后参考。
              </p>
              <p>
               下次聚会计划讨论R和数据库接口部分，集中RODBC和RSQLite这两个包；MASS线形模型这章，主要集中介绍R中统计模型的formulea设计的问题。
              </p>
              <p>
               考虑到西南财大那边一起讨论的朋友偏重金融计量方面，除了MASS涉及统计建模前面几章外，将主要依据计量经济学中一系列经典教材的示例用R实现这一主题来展开。
               <br/>
               如果对时间序列等有兴趣的人多的话，将讨论《时间序列与金融数据分析》（陈毅恒）一书，或者采用FinMetrics包的附带教材作为学习交流的主要材料。
               <br/>
               诸位R/S的兴趣爱好者也可以给我们多多提供意见和建议，谢谢。
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               2007年1月21日 上午3:25
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               昨天由于有事，未能参与最后一次学习。。错过了。
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               2007年1月21日 上午10:42
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              <p>
               1月20日在西南财大进行了本学期最后一次R/S的聚会。主要涉及R数据库接口方面的内容，并介绍了R的各种脚本编辑器以及GUI界面和开发工具。春节后学期开始，将继续进行讨论活动，欢迎大家参加并提供各自的意见和建议。
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